Directory Indexer
Transforms local directories into an AI-powered knowledge base, enabling semantic search for documents based on meaning.
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Directory Indexer converts your local file directories into a powerful, AI-powered knowledge base, allowing for advanced semantic search capabilities. By indexing your documents based on their meaning rather than just filenames, it empowers AI assistants and users to quickly locate relevant information. This tool integrates seamlessly with AI clients via an MCP server, leveraging external components like Qdrant for vector storage and various embedding providers for intelligent indexing, transforming how you interact with your personal or team's file archives.
Características Principales
- Perform semantic search across local files and directories
- Integrate with AI assistants (e.g., Claude Desktop) via MCP server
- Support for various file types including text, code, data, and configuration files
- Flexible embedding provider options, including self-hosted Ollama and OpenAI
- CLI for indexing, searching, finding similar files, and retrieving content
- 1 GitHub stars
Casos de Uso
- Enable AI assistants to perform intelligent, semantic searches on local file systems.
- Quickly locate relevant documents and code snippets within large directories based on their content's meaning.
- Create a comprehensive, searchable knowledge base from personal or team file archives.
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